找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Geometry of Deep Learning; A Signal Processing Jong Chul Ye Textbook 2022 The Editor(s) (if applicable) and The Author(s), under exclusive

[复制链接]
查看: 46778|回复: 53
发表于 2025-3-21 18:57:49 | 显示全部楼层 |阅读模式
书目名称Geometry of Deep Learning
副标题A Signal Processing
编辑Jong Chul Ye
视频video
概述Covers recent developments in deep learning and a wide spectrum of issues, with exercise problems for students.Employs unified mathematical approaches with illustrative graphics to present various tec
丛书名称Mathematics in Industry
图书封面Titlebook: Geometry of Deep Learning; A Signal Processing  Jong Chul Ye Textbook 2022 The Editor(s) (if applicable) and The Author(s), under exclusive
描述.The focus of this book is on providing students with insights into geometry that can help them understand deep learning from a unified perspective. Rather than describing deep learning as an implementation technique, as is usually the case in many existing deep learning books, here, deep learning is explained as an ultimate form of signal processing techniques that can be imagined. .To support this claim, an overview of classical kernel machine learning approaches is presented, and their advantages and limitations are explained. Following a detailed explanation of the basic building blocks of deep neural networks from a biological and algorithmic point of view, the latest tools such as attention, normalization, Transformer, BERT, GPT-3, and others are described. Here, too, the focus is on the fact that in these heuristic approaches, there is an important, beautiful geometric structure behind the intuition that enables a systematic understanding. A unified geometric analysis to understand the working mechanism of deep learning from high-dimensional geometry is offered. Then, different forms of generative models like GAN, VAE, normalizing flows, optimal transport, and so on are desc
出版日期Textbook 2022
关键词Deep learning; Mathematical principle of deep learning; Geometric understanding of deep neural network
版次1
doihttps://doi.org/10.1007/978-981-16-6046-7
isbn_softcover978-981-16-6048-1
isbn_ebook978-981-16-6046-7Series ISSN 1612-3956 Series E-ISSN 2198-3283
issn_series 1612-3956
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

书目名称Geometry of Deep Learning影响因子(影响力)




书目名称Geometry of Deep Learning影响因子(影响力)学科排名




书目名称Geometry of Deep Learning网络公开度




书目名称Geometry of Deep Learning网络公开度学科排名




书目名称Geometry of Deep Learning被引频次




书目名称Geometry of Deep Learning被引频次学科排名




书目名称Geometry of Deep Learning年度引用




书目名称Geometry of Deep Learning年度引用学科排名




书目名称Geometry of Deep Learning读者反馈




书目名称Geometry of Deep Learning读者反馈学科排名




单选投票, 共有 1 人参与投票
 

0票 0.00%

Perfect with Aesthetics

 

1票 100.00%

Better Implies Difficulty

 

0票 0.00%

Good and Satisfactory

 

0票 0.00%

Adverse Performance

 

0票 0.00%

Disdainful Garbage

您所在的用户组没有投票权限
发表于 2025-3-21 20:40:46 | 显示全部楼层
发表于 2025-3-22 00:59:02 | 显示全部楼层
发表于 2025-3-22 07:48:14 | 显示全部楼层
发表于 2025-3-22 11:03:32 | 显示全部楼层
发表于 2025-3-22 15:53:57 | 显示全部楼层
Einführung in die Volkswirtschaftslehreks, brain networks, molecule networks, etc. See some examples in Fig. 8.1. In fact, the complex interaction in real systems can be described by different forms of graphs, so that graphs can be a ubiquitous tool for representing complex systems.
发表于 2025-3-22 19:46:51 | 显示全部楼层
发表于 2025-3-22 23:00:12 | 显示全部楼层
发表于 2025-3-23 05:10:05 | 显示全部楼层
发表于 2025-3-23 08:12:49 | 显示全部楼层
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-22 17:23
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表